NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Type
Journal Articles8
Reports - Research8
Tests/Questionnaires8
Audience
Teachers1
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 8 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Barb Bennie; Richard A. Erickson – Journal of Statistics and Data Science Education, 2024
Effective undergraduate statistical education requires training using real-world data. Textbook datasets seldom match the complexities and messiness of real-world data and finding these datasets can be challenging for educators. Consulting and industrial datasets often have nondisclosure agreements. Academic datasets often require subject area…
Descriptors: Undergraduate Students, Statistics Education, Data Science, Earth Science
Peer reviewed Peer reviewed
Direct linkDirect link
Wilkerson, Michelle Hoda; Lanouette, Kathryn; Shareff, Rebecca L. – Mathematical Thinking and Learning: An International Journal, 2022
Data preparation (also called "wrangling" or "cleaning") -- the evaluation and manipulation of data prior to formal analysis -- is often dismissed as a precursor to meaningful engagement with a dataset. Here, we re-envision data preparation in light of calls to prepare students for a data-rich world. Traditionally, curricular…
Descriptors: Data Science, Information Literacy, Data Analysis, Secondary School Students
Peer reviewed Peer reviewed
Direct linkDirect link
Jo Boaler; Kira Conte; Ken Cor; Jack A. Dieckmann; Tanya LaMar; Jesse Ramirez; Megan Selbach-Allen – Journal of Statistics and Data Science Education, 2025
This article reports on a multi-method study of a high school course in data science, finding that students who take data science take more mathematics courses than those who do not, there are more under-represented students in data science than is typical for other advanced mathematics courses; that the students who take data science are more…
Descriptors: Mathematics Instruction, Opportunities, High School Students, Data Science
Peer reviewed Peer reviewed
Direct linkDirect link
Crystal Goldman; Erik T. Mitchell – portal: Libraries and the Academy, 2024
The intersection of Data Science (DS) and Library and Information Science (LIS) is rapidly developing, with a notable need for ongoing transdisciplinary training between practitioners in these two fields. The LIS Education and Data Science Integrated Network Group (LEADING) fellowship program and its ancillary community of practice (CoP) showcase…
Descriptors: Library Science, Information Science Education, Data Science, Interdisciplinary Approach
Peer reviewed Peer reviewed
Direct linkDirect link
Alex Duran-Riquelme; Cherie Flores-Fernández; Judith Riquelme-Ríos – Education for Information, 2024
A professional practice is a type of internship, a practicum, that encompasses a supervised hands-on training experience for students to develop and identify the core and enabling competencies required in a professional environment. It also allows them to identify the developed and underdeveloped skills that are important in the labour environment…
Descriptors: Graduate Students, Library Science, Internship Programs, Practicums
Peer reviewed Peer reviewed
Direct linkDirect link
Ibrahim Oluwajoba Adisa; Danielle Herro; Oluwadara Abimbade; Golnaz Arastoopour Irgens – Information and Learning Sciences, 2024
Purpose: This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms. Design/methodology/approach: This paper describes a pedagogical approach that uses a data science…
Descriptors: Learner Engagement, Elementary School Students, Data Science, Computation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Jose L. Salas; Xinran Wang; Mary C. Tucker; Ji Y. Son – Online Learning, 2024
Students believe mathematics is best learned by memorization; however, endorsing memorization as a study strategy is associated with a decrease in learning (Schoenfeld, 1989). When the world changed with the onset of the COVID-19 global pandemic, instruction transitioned to fully remote instruction where many assignments and examinations became…
Descriptors: Distance Education, Memorization, Pandemics, COVID-19
Peer reviewed Peer reviewed
Direct linkDirect link
Anna Khalemsky; Yelena Stukalin – Statistics Education Research Journal, 2024
The article describes the inclusive perspective of instruction of multi-stage practical projects in undergraduate non-STEM statistics and data mining courses at an academic college in Israel. The student population is highly diverse, comprising individuals from various cultural and ethnic groups. The study examines the impact of diversity on…
Descriptors: Foreign Countries, Undergraduate Students, Statistics Education, Data Science